Browsing by Author "Olaide, Fagbolu Olutola"
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- ItemAndroid platform for machine translation -a focus on Yorùbá Language(American Journal of Computation, Communication and Control 2018; 5(1): 16-23, 2018-01) Olaide, Fagbolu Olutola; Kayode, Alese Boniface; Adewale, Olumide Sunday; Adetunmbi, Adebayo OlusolaAndroid platform provides useful words and phrases in English language, with translations in Yorùbá language, for the use of visitors to places where the language is spoken; it can be likened to bilingual dictionary of English-Yorùbá. It is developed on Mobile platform for easier accessibility, convenience and portability. Rough Set Theory (RST) is the mathematical tool used in decision support and data analysis of words or phrases that are to be translated. Comparisons between query that is, word or phrase to be translated, are made with the created corpus, using RST. Programming tools employed for mobile platform are JDK 6, Apache Ant 1.8 or later, Android Software Development Kit, Eclipse Integrated Development Environment, Android Developer and Android Studio while latest technologies such as PHP, Mysql,. net, Mssql 2005, 2008, Ajax techies, C#. It brings the usefulness of Information Technology to the doorstep of non- Yorùbá tourists or learners who wish to converse, make friends with Yorùbá people or transact business with Yorùbá indigenes that are not literate. It was found after its deployment to be intelligible and accurate with minimal errors. New words and expressions that are suitable for situations, legislation, science, engineering, commerce, computing, mass communication and other sphere of life were created in a large number.
- ItemAutomated Personal Clinic Services in Uganda Software Requirement Specification(Department of Computer Science, School of Computing & Information Technology, Kampala International University, Kampala, Uganda, 2018) Olaide, Fagbolu Olutola; Nyadru, InnocentSoftware Requirement Specification for Personal Clinic Services enhance the availability and accessibility of traditional clinic, health care services are offer without limits or physical boundary, it is a web-based mobile Chatbot in google assistant that help patients to find closest clinics and hospitals in Uganda, offers medical prescription and other forms of medical assistances. It consists of three (3) parts which are Chatbot, Google home device and web portal. The google assistant guide was employed in the design using predefined procedures as Google application, Google app tool, PHP (Hypertext Preprocessor) which by default comes as handy tool with every android and it requires internet and Global Positioning System (GPS) connection. Few datasets were trained for machine learning using supervised learning category and other coding were done online. Personal Clinic prototype was simulated to provide basics of health care services to the prospective clients, doctors within the patient’s locality are contacted for further medical assistance whenever the need arises. Most of healthcare challenges would be solved and life expectancy would increase with greater capability to live healthier, longer and reduced the risk of patient harm.
- ItemMobile Recruitment System for Nigerian Civil Service Commission via Cloud Computing(Department of Computer Science, School of Computing and Information Technology, Kampala International University, Kampala, Uganda, 2018-04-07) Olaide, Fagbolu Olutola; Oluwatobi, Atoloye AfeezTraditional recruitment procedures are replaced in order to overcome most of its attendant challenges such as time-consuming and tiresome nature of recruiting a larger number of applicants into Civil Service from different parts of Nigeria considering multifaceted nature of the nation. This research work obliterate favouritism, nepotism and other corrupt means that were the usual practice in shortlisting prospective candidate for job, electronic recruitment system are enhanced with the availability of mobile platform that improve accessibility with emerging computing paradigm over the internet. Finite State Transducer (FST) in Machine Learning is used to learn from the pool of candidates for employment, GIATI(Grammar Inference and Alignment for Transducers Inference) are efficiently applied that is prospective candidates are offered job on a deductive rule-based Machine Learning. It is implemented with Android Studio and WAMP server. Its performance was tested using Ogun State as a pilot in the Federation and User Satisfaction were evaluated.